Title :
A dataflow processing element for neural network simulation
Author :
Mutlaq, M. Abu ; Braham, R.
Author_Institution :
Dept. of Comput. Eng., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
Abstract :
Neural networks can be easily represented by macro dataflow graphs. Dataflow machines are thus suitable for simulation of these networks. In this paper, neural computing hardware considerations are first addressed. The architecture of a new argument-fetch dataflow processor dedicated to neural computing is then described. Backpropagation and Hopfield networks are transformed into dataflow graphs and simulated on the machine. Excellent performance results have been achieved
Keywords :
Hopfield neural nets; backpropagation; data flow graphs; neural net architecture; performance evaluation; simulation; virtual machines; Hopfield networks; architecture; argument-fetch dataflow processor; backpropagation; dataflow processing; macro dataflow graphs; performance evaluation; simulation; Artificial neural networks; Backpropagation; Computational modeling; Computer architecture; Computer networks; Computer simulation; Concurrent computing; Distributed computing; Hardware; Neural network hardware; Neural networks; Neurons; Scalability;
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
DOI :
10.1109/ICNN.1995.488133
